Bias Considerations in Simulation Experiments
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This paper uses a first-order autoregressive scheme to investigate the effects of initial conditions in a simulation on the estimation of the population mean of a process of interest. The effects are measured by bias and variance. The results show that the elimination of observations near the beginning of the simulation reduces bias, as intended, but increases the variance, sometimes significantly.
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